{"total":53,"rows":[{"id":"2305.15347","title":"A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence","created":"2023-05-24","cited_by_count":301,"area":"diffusion"},{"id":"2303.11797","title":"CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation","created":"2023-03-21","cited_by_count":219,"area":null},{"id":"2305.14334","title":"Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence","created":"2023-05-23","cited_by_count":214,"area":"diffusion"},{"id":"2311.03335","title":"Cross-Image Attention for Zero-Shot Appearance Transfer","created":"2023-11-06","cited_by_count":136,"area":null},{"id":"2305.15581","title":"Unsupervised Semantic Correspondence Using Stable Diffusion","created":"2023-05-24","cited_by_count":120,"area":"diffusion"},{"id":"2311.17034","title":"Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence","created":"2023-11-28","cited_by_count":86,"area":null},{"id":"2407.15420","title":"Local All-Pair Correspondence for Point Tracking","created":"2024-07-22","cited_by_count":80,"area":null},{"id":"2410.22128","title":"PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting","created":"2024-10-29","cited_by_count":62,"area":null},{"id":"2402.09812","title":"DreamMatcher: Appearance Matching Self-Attention for Semantically-Consistent Text-to-Image Personalization","created":"2024-02-15","cited_by_count":60,"area":"diffusion"},{"id":"2509.07979","title":"Visual Representation Alignment for Multimodal Large Language Models","created":"2025-09-09","cited_by_count":41,"area":"lr"},{"id":"2312.07246","title":"Unifying Correspondence, Pose and NeRF for Pose-Free Novel View Synthesis from Stereo Pairs","created":"2023-12-12","cited_by_count":37,"area":null},{"id":"2210.02689","title":"Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence","created":"2022-10-06","cited_by_count":32,"area":null},{"id":"2506.17220","title":"Emergent Temporal Correspondences from Video Diffusion Transformers","created":"2025-06-20","cited_by_count":31,"area":"diffusion"},{"id":"2412.09072","title":"Cross-View Completion Models are Zero-shot Correspondence Estimators","created":"2024-12-12","cited_by_count":30,"area":null},{"id":"2509.18096","title":"Seg4Diff: Unveiling Open-Vocabulary Segmentation in Text-to-Image Diffusion Transformers","created":"2025-09-22","cited_by_count":24,"area":"diffusion"},{"id":"2209.11047","title":"MIDMs: Matching Interleaved Diffusion Models for Exemplar-based Image Translation","created":"2022-09-22","cited_by_count":22,"area":"diffusion"},{"id":"2512.04012","title":"Emergent Outlier View Rejection in Visual Geometry Grounded Transformers","created":"2025-12-03","cited_by_count":22,"area":null},{"id":"2305.19094","title":"Diffusion Model for Dense Matching","created":"2023-05-30","cited_by_count":21,"area":"diffusion"},{"id":"2512.04021","title":"C3G: Learning Compact 3D Representations with 2K Gaussians","created":"2025-12-03","cited_by_count":21,"area":null},{"id":"2311.14671","title":"SEGIC: Unleashing the Emergent Correspondence for In-Context Segmentation","created":"2023-11-24","cited_by_count":19,"area":null},{"id":"2412.03512","title":"Distillation of Diffusion Features for Semantic Correspondence","created":"2024-12-04","cited_by_count":17,"area":null},{"id":"2403.11120","title":"Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence","created":"2024-03-17","cited_by_count":14,"area":null},{"id":"2501.14945","title":"MATCHA:Towards Matching Anything","created":"2025-01-24","cited_by_count":12,"area":null},{"id":"2504.06264","title":"D$^2$USt3R: Enhancing 3D Reconstruction for Dynamic Scenes","created":"2025-04-08","cited_by_count":10,"area":null},{"id":"2503.22462","title":"SemAlign3D: Semantic Correspondence between RGB-Images through Aligning 3D Object-Class Representations","created":"2025-03-28","cited_by_count":7,"area":null},{"id":"2506.13697","title":"Vid-CamEdit: Video Camera Trajectory Editing with Generative Rendering from Estimated Geometry","created":"2025-06-16","cited_by_count":7,"area":null},{"id":"2209.08742","title":"Integrative Feature and Cost Aggregation with Transformers for Dense Correspondence","created":"2022-09-19","cited_by_count":6,"area":null},{"id":"2506.08220","title":"Jamais Vu: Exposing the Generalization Gap in Supervised Semantic Correspondence","created":"2025-06-09","cited_by_count":6,"area":null},{"id":"2506.09993","title":"Text-Aware Image Restoration with Diffusion Models","created":"2025-06-11","cited_by_count":6,"area":"diffusion"},{"id":"2508.00746","title":"GECO: Geometrically Consistent Embedding with Lightspeed Inference","created":"2025-08-01","cited_by_count":6,"area":null},{"id":"2504.05301","title":"S^4M: Boosting Semi-Supervised Instance Segmentation with SAM","created":"2025-04-07","cited_by_count":5,"area":null},{"id":"2603.17520","title":"PCA-Seg: Revisiting Cost Aggregation for Open-Vocabulary Semantic and Part Segmentation","created":"2026-03-18","cited_by_count":5,"area":"mllm"},{"id":"2501.09688","title":"Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation","created":"2025-01-16","cited_by_count":4,"area":null},{"id":"2604.04050","title":"TORA: Topological Representation Alignment for 3D Shape Assembly","created":"2026-04-05","cited_by_count":4,"area":"diffusion"},{"id":"2306.04231","title":"Learning Probabilistic Coordinate Fields for Robust Correspondences","created":"2023-06-07","cited_by_count":3,"area":null},{"id":"2306.05749","title":"DocAligner: Annotating Real-world Photographic Document Images by Simply Taking Pictures","created":"2023-06-09","cited_by_count":3,"area":null},{"id":"2505.18060","title":"Semantic Correspondence: Unified Benchmarking and a Strong Baseline","created":"2025-05-23","cited_by_count":3,"area":null},{"id":"2604.18267","title":"MARCO: Navigating the Unseen Space of Semantic Correspondence","created":"2026-04-20","cited_by_count":3,"area":null},{"id":"2311.18540","title":"Match me if you can: Semi-Supervised Semantic Correspondence Learning with Unpaired Images","created":"2023-11-30","cited_by_count":2,"area":null},{"id":"2605.22190","title":"No Pose, No Problem in 4D: Feed-Forward Dynamic Gaussians from Unposed Multi-View Videos","created":"2026-05-21","cited_by_count":2,"area":null},{"id":"2605.31595","title":"Learning Global Motion with Compact Gaussians for Feed-Forward 4D Reconstruction","created":"2026-05-29","cited_by_count":2,"area":null},{"id":"2503.22019","title":"AGILE: A Diffusion-Based Attention-Guided Image and Label Translation for Efficient Cross-Domain Plant Trait Identification","created":"2025-03-27","cited_by_count":1,"area":null},{"id":"2509.24318","title":"Similarity-Aware Selective State-Space Modeling for Semantic Correspondence","created":"2025-09-29","cited_by_count":1,"area":"ssm"},{"id":"2605.03175","title":"DINO Soars: DINOv3 for Open-Vocabulary Semantic Segmentation of Remote Sensing Imagery","created":"2026-05-04","cited_by_count":1,"area":null},{"id":"2306.10208","title":"Learning Space-Time Semantic Correspondences","created":"2023-06-16","cited_by_count":0,"area":null},{"id":"2403.08227","title":"Matching Semantically Similar Non-Identical Objects","created":"2024-03-13","cited_by_count":0,"area":null},{"id":"2508.00272","title":"Towards Robust Semantic Correspondence: A Benchmark and Insights","created":"2025-08-01","cited_by_count":0,"area":null},{"id":"2508.21090","title":"Q-Align: Alleviating Attention Leakage in Zero-Shot Appearance Transfer via Query-Query Alignment","created":"2025-08-27","cited_by_count":0,"area":null},{"id":"2602.03105","title":"Gromov Wasserstein Optimal Transport for Semantic Correspondences","created":"2026-02-03","cited_by_count":0,"area":"diffusion"},{"id":"2606.16569","title":"PROSE: Training-Free Egocentric Scene Registration with Vision-Language Models","created":"2026-06-15","cited_by_count":0,"area":"mllm"},{"id":"2607.02968","title":"Awakening Diffusion Transformers: Eliciting Stronger Generation and Understanding via Massive Activation Modulation","created":"2026-07-03","cited_by_count":0,"area":"diffusion"},{"id":"2608.29121","title":"Acoustically Grounded Cost Learning for Open-Vocabulary Audio-Visual Semantic Segmentation","created":"2026-08-29","cited_by_count":0,"area":null},{"id":"2609.15357","title":"Diffusion Trajectory Modeling for Semantic Correspondence","created":"2026-09-14","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}